Apache Hudi, originally developed by Uber in 2016, was created to support the growth of the ride-sharing platform by establishing a transactional data lake capable of handling updates efficiently. It is now widely utilized in the industry for building large-scale data lakes, known for its fast incremental updates and robust services layer. By providing online transaction processing database functionality to data stored in a data lake, Apache Hudi enables users to store massive amounts of data with the cost efficiency of a cloud object store. Additionally, it offers data lineage, integration with access control and governance mechanisms, and incremental data ingestion for near real-time performance.
AWS has integrated Apache Hudi into various services like Amazon EMR, Amazon Athena, and Amazon Redshift, making it easier for users to leverage Hudi’s capabilities in their AWS environments. AWS Data Exchange, a service provided by AWS, allows users to find, subscribe to, and use third-party datasets in the AWS Cloud, offering a platform for data producers to make their data available for consumption.
By combining Apache Hudi with AWS Data Exchange, users can establish a single source of truth for transactional data and enable automatic business value generation. This setup can be achieved in the AWS environment using Amazon S3, Amazon EMR, Amazon Athena, and AWS Data Exchange. Setting up data sharing capabilities in AWS Data Exchange on top of Apache Hudi allows for enhanced data collaboration and improved customer experience.
To publish a product using a registered Hudi dataset on AWS Data Exchange, providers need to create datasets, define access rules, provide product information, and configure pricing details. Subscribing to shared datasets on AWS Data Exchange enables users to access the data for analytics and data science applications. Additionally, creating tables in Athena using an Amazon S3 access point allows users to run analytical queries using Athena SQL statements.
Overall, the integration of Apache Hudi and AWS Data Exchange offers numerous benefits for users, such as near real-time updated datasets and incremental pipelines and processing. Following best practices for security and compliance, like enabling AWS Lake Formation and using CloudWatch logs, ensures secure and efficient data management. Lastly, the collaboration between AWS Data Exchange and Apache Hudi unlocks business value and accelerates outcomes in various use cases.
Article Source
https://aws.amazon.com/blogs/big-data/use-aws-data-exchange-to-seamlessly-share-apache-hudi-datasets/